code: def __init__(
      self,
      bound: int,
      encoder_num_input_dims: int,
      encoder_cfg: Dict,
      background_net_num_output_dims: int,
      background_net_cfg: Dict,
  ):
      super().__init__()
      self.bound = bound
      if encoder_cfg.get("per_level_scale") is None:
          encoder_cfg["per_level_scale"] = np.exp2(
              np.log2(2048 * self.bound / 16) / (16 - 1)
          )
      self.encoder = tcnn.Encoding(
          n_input_dims=encoder_num_input_dims,
          encoding_config=dict(encoder_cfg),
      )
      self.background_net = tcnn.Network(
          self.encoder.n_output_dims,
          background_net_num_output_dims,
          network_config=dict(background_net_cfg),
      )
  
file_path: NeMo/nemo/collections/multimodal/modules/nerf/background/tcnn_background.py
imports: from typing import Dict
  import numpy
  import tinycudann
  import torch
  from nemo.collections.multimodal.modules.nerf.background.nerf_background_base import NeRFBackgroundBase
label_desc: Use image node_id 1 to create a new TCNNBackground object from inherited base classes: NeRFBackgroundBase with example: obj = TCNNBackground(bound, encoder_num_input_dims, encoder_cfg, background_net_num_output_dims, background_net_cfg)